Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, UK.

10

Department of Morphology, Institute of Biosciences of Botucatu, Sao Paulo State University (UNESP), Sao Paulo, Brazil.

Abstract

Genetically engineered mouse models of cancer can be used to filter genome-wide expression datasets generated from human tumours and to identify gene expression alterations that are functionally important to cancer development and progression. In this study, we have generated RNAseq data from tumours arising in two established mouse models of prostatecancer, PB-Cre/PtenloxP/loxP and p53loxP/loxPRbloxP/loxP, and integrated this with published human prostatecancer expression data to pinpoint cancer-associated gene expression changes that are conserved between the two species. To identify potentialtherapeutictargets, we then filtered this information for genes that are either known or predicted to be druggable. Using this approach, we revealed a functional role for the kinase MELK as a driver and potentialtherapeutic target in prostatecancer. We found that MELK expression was required for cell survival, affected the expression of genes associated with prostatecancer progression and was associated with biochemical recurrence.

Transcriptomic landscape of prostate tumours arising in the PB‐Cre/PtenloxP/loxP and PB‐Cre/p53loxP/loxPRbloxP/loxP models

Sample distance heatmap showing the clustering of normal tissue, PIN, medium‐stage tumours (MedTumour) and advanced‐stage tumours (AdTumour) derived from the four murine prostatic lobes in PB‐Cre/PtenloxP/loxP mice based on their gene expression profile as assessed by RNA sequencing.Sample distance heatmap showing the clustering of normal tissue and PIN derived from the four murine prostatic lobes and aggressive, proximal zone‐derived tumours in PB‐Cre/p53loxP/loxPRbloxP/loxP mice based on their gene expression profile as assessed by RNA sequencing.Venn diagrams showing the derivation of PIN‐, MedTumour‐ and AdTumour‐associated gene expression signatures in the PB‐Cre/PtenloxP/loxP model. Differentially expressed genes (DEG) in PIN, medium‐stage tumours and advanced‐stage tumours of all lobes were identified relative to their respective wild‐type lobe of origin (Padj < 0.05). Genes that were significantly upregulated or downregulated in PIN, medium‐stage tumours or advanced‐stage tumours in all four lobes are depicted in heatmaps.Overlaps between the PIN, MedTumour and AdTumour gene expression signatures. PIN: prostatic intraepithelial neoplasia; MedTumour: medium‐stage tumour; AdTumour: advanced‐stage tumour.MetaCore™ enrichment analyses for process networks on three gene sets: aberrantly expressed in all three stages of tumour progression (“All Stages”, n = 351); aberrantly expressed in both medium‐stage and advanced‐stage tumours, but not in PIN lesions (“Tumour‐Specific”, n = 220); aberrantly expressed in advanced‐stage tumours only (“AdTumour‐specific”, n = 384). For each gene set, significantly enriched process networks (P < 0.01) were ranked according to their P‐value. The lists of enriched process network terms were combined, and their ranks across all three gene sets are shown as a heatmap. n.s.: not significantly enriched in this gene set. Source data are available online for this figure.

Identification of potentialtherapeutictargets in prostatecancer using cross‐species analysis

Expression patterns of the Cuzick signature mouse homologous genes in prostate tumours arising in the PB‐Cre/PtenloxP/loxP and PB‐Cre/p53loxP/loxPRbloxP/loxP models.Gene set enrichment analyses (GSEAs) comparing genes upregulated or downregulated in both mouse models to the Grasso human prostatecancer dataset. NES: normalised enrichment score; PCa: prostatecancer.Strategy to identify potentialtherapeutictargets in prostatecancer. Genes that are upregulated in cancers of both mouse models (“Pten model (all lobes) and p53/Rb model” in Fig A) are identified, and this consensus signature is then compared to the Grasso human prostatecancer expression dataset using GSEA. Genes forming the core enrichment in this analysis are filtered for druggability using The Drug Gene Interaction Database (DGIdb). The association of the expression of the resulting candidate genes with poor outcome is then used to refine the list.Potentialtherapeutictargets identified using the strategy outlined in (C). The expression levels of the candidate genes in prostate tumours of the PB‐Cre/PtenloxP/loxP and PB‐Cre/p53loxP/loxPRbloxP/loxP models are depicted as heatmaps. Source data are available online for this figure.

Similarities between human and murine prostatecancer facilitate identification of potentialtherapeutictargets

Expression patterns of the Hes6 signature (Ramos‐Montoya et al, ) mouse homologous genes in prostate tumours arising in the PB‐Cre/PtenloxP/loxP and PB‐Cre/p53loxP/loxPRbloxP/loxP models.Gene set enrichment analysis was used to compare various subsets of genes altered in mouse prostatecancer to the Grasso dataset of human prostatecancer (Grasso et al, ). Dotted lines indicate the NES obtained using the gene set “Pten model (all lobes) and p53/Rb model”. A significance cut‐off of Padj < 0.05 was used for all gene sets. Normalised enrichment scores < 0: gene set enriched in human prostate tumours; normalised enrichment score > 0: gene set enriched in benign human prostate tissue. Due to the large number of DEGs in the p53/pRb model, only the top 500 significantly upregulated and downregulated genes each were used for this gene set.

Effect of OTS167 on MELK targets. C4‐2b cells were treated with 15, 30 or 60 nM OTS167 for 1 and 24 h. Phosphorylation of ACC at Ser‐79 and MELK protein levels were determined by Western blot analysis. β‐Actin was used as a loading control.Validation of MELK knock‐down by three siRNAs. C4‐2b cells were transfected with siRNAs, and after 48 h, MELK levels were determined by Western blot analysis. β‐Actin was used as a loading control.Venn diagrams showing the overlaps between genes altered following silencing or inhibition of MELK. C4‐2b cells were transfected with siRNAs directed against MELK for 72 h, or treated with 30 nM OTS167 for 8 and 24 h, and subjected to RNA sequencing (n = 4). Differentially expressed genes were identified compared to samples transfected with control siRNA or treated with vehicle, respectively (Padj < 0.05).Expression of MELK in Hes6‐overexpressing LNCaP xenografts (Ramos‐Montoya et al, ).Effect of silencing of MELK on proliferation of prostatecancer cells. LNCaP cells were transfected with siRNAs directed against MELK or a non‐targeting control, and viable cells were counted after 4 and 7 days. n = 4. Statistical significance was assessed by randomised blocks ANOVA (significance threshold of 0.05) followed by Holm–Sidak's multiple comparisons test.Effect of OTS167 on proliferation of prostatecancer cells. LNCaP cells were treated with vehicle or OTS167 at varying concentrations, and viable cells were counted after 2 and 5 days. n = 3. Statistical significance was assessed by randomised blocks ANOVA (significance threshold of 0.05) followed by Holm–Sidak's multiple comparisons test.OTS167 reduces proliferation of five prostatecancer cell lines and one non‐transformed prostate cell line at nanomolar concentrations. Cells were treated with vehicle or OTS167 in concentrations ranging from 60 pM to 4.1 μM. After 72 h, viability was quantified by MTS assay and IC50 values were calculated. n = 2, with six technical replicates per biological replicate. Source data are available online for this figure.

GSEA comparing genes repressed by both silencing and inhibition of MELK to the Grasso human prostatecancer dataset. C4‐2b cells were transfected with siRNAs directed against MELK for 72 h, or treated with 30 nM OTS167 for 8 and 24 h, and subjected to RNA sequencing (n = 4). Genes that were significantly downregulated (Padj < 0.05) by both siRNAs and by OTS167 at at least one time point were considered as positively regulated by MELK. NES: normalised enrichment score; PCa: prostatecancer; Met: metastases.Overlap between MELK‐regulated genes and Hes6 signature (Ramos‐Montoya et al, ).Altered process networks following MELK abrogation. Differentially expressed genes for each treatment condition were identified (Padj < 0.05), and the 50 most enriched process networks in each condition were computed using Metacore enrichment analysis. Enriched process networks were ranked according to their P‐value, and the ranks of the 10 most enriched process networks across all four conditions were visualised as a heatmap.Effect of silencing of MELK on proliferation of prostatecancer cells. C4‐2b cells were transfected with siRNAs directed against MELK or a non‐targeting control, and viable cells were counted after 4 and 7 days. n = 4.Effect of OTS167 on proliferation of prostatecancer cells. C4‐2b cells were treated with vehicle or OTS167 at varying concentrations, and viable cells were counted after 2 and 5 days. n = 3.Correlation between MELK expression and sensitivity to OTS167. MELK mRNA levels in prostate cell lines were determined by qRT–PCR, n = 4 for all cell lines, except C4‐2b (n = 5). The IC50 for OTS167 in each cell line was determined (see Fig F). The correlation between MELK expression and OTS167 IC50 was assessed by Pearson correlation coefficient.Effect of OTS167 on clonogenic ability of prostatecancer cells. C4‐2b cells were seeded at low confluence and grown in presence of vehicle or varying concentrations of OTS167 for 9 days. Colonies were stained with crystal violet, and total colony volume was quantified. n = 3.Data information: Statistical significance was assessed by randomised blocks ANOVA (significance threshold of 0.05) followed by Holm–Sidak's multiple comparisons test in panels (D, E and G).Source data are available online for this figure.

OTS167 reduces growth of prostatecancer xenografts. Luciferase‐expressing C4‐2b xenograft tumours were established in NOD scid gamma mice for 7 days. Animals were subsequently dosed with 10 mg/kg OTS167 i.p. daily. Bioluminescence was measured once per week. n = 10. Statistical significance was assessed using the Holm–Sidak method (α = 5%). Arrow indicates start of dosing with vehicle or OTS167.The growth of xenografts in (A) was followed by calliper measurements twice per week from day 10, when tumours first became palpable. n = 10. Statistical significance was assessed using the Holm–Sidak method (α = 5%).Xenograft tumours in (A) were weighed after sacrifice. n = 10 for vehicle group, n = 8 for OTS167 group. Statistical significance was assessed by Mann–Whitney test. Horizontal line indicates median; box limits correspond to 75th and 25th percentiles; whiskers indicate minimum and maximum.Effect of OTS167 on apoptosis of xenograft tumours. Xenograft tumours were stained for cleaved caspase‐3 (CC3) as a read‐out for apoptosis induction, and CC3‐positive cells were quantified. n = 10 for vehicle group; n = 8 for OTS167 group. Statistical significance was assessed by Mann–Whitney test. Scale bars correspond to 200 μm. Horizontal line indicates median; box limits correspond to 75th and 25th percentiles; whiskers indicate minimum and maximum.Effect of OTS167 on apoptosis of prostatecancer cells. C4‐2b cells were treated with vehicle or OTS167 at varying concentrations for 48 h, and apoptotic, live and dead cells were quantified by Annexin V/propidium iodine staining followed by flow cytometry analysis. Statistical significance of the differences between the proportions of apoptotic cells was tested by randomised blocks ANOVA (significance threshold of 0.05) followed by Holm–Sidak's multiple comparisons test. n = 3.Effect of MELK siRNA on apoptosis of prostatecancer cells. C4‐2b cells were transfected with siRNAs directed against MELK for 4 days, and apoptotic, live and dead cells were quantified by Annexin V/propidium iodine staining followed by flow cytometry analysis. Statistical significance of the differences between the proportions of apoptotic cells was tested by randomised blocks ANOVA (significance threshold of 0.05) followed by Holm–Sidak's multiple comparisons test. n = 4. Source data are available online for this figure.

Inhibition of MELK reduces phosphorylation of stathmin and interferes with mitotic spindle formation

Identification of phosphorylation sites affected by OTS167. C4‐2b cells were treated with vehicle or 30 nM OTS167 for 2 h, and phosphoproteins were analysed using a Phospho Explorer Antibody Array. Signals for each phosphorylation site were normalised to its corresponding total protein. Top upregulated and downregulated phosphorylation sites are shown. n = 1.Validation of effects of OTS167 on phosphorylation of p90RSK and its targets. C4‐2b cells were treated with vehicle or 30 nM OTS167 for the indicated times, and levels of total and phosphorylated proteins were determined by Western blot analysis. β‐Actin was used as a loading control.Treatment with OTS167 reduces phosphorylation of stathmin at Ser‐38. C4‐2b cells were treated with vehicle or 30 nM OTS167 for the indicated times, and levels of total and phosphorylated stathmin were determined by Western blot analysis. β‐Actin was used as a loading control.Treatment with OTS167 results in formation of abnormal mitotic spindles. C4‐2b cells were treated with vehicle or 30 nM OTS167 for 24 h. Mitotic spindles and DNA were visualised by immunofluorescent staining for α‐tubulin, and by staining with DAPI, respectively. Scale bars correspond to 10 μm. For vehicle‐treated cells, examples of normal metaphase (I), anaphase (II) and telophase (III) are shown. For OTS167‐treated cells, normal mitotic phases could not be observed. Note mis‐attached chromosomes (arrows). Intact and defective spindles were quantified by counting 100 mitotic cells per experimental condition. Significance was assessed using the chi‐square test. Source data are available online for this figure.

Identification and validation of downstream pathways regulated by MELK

Phosphorylation sites on p90RSK and its substrates affected by OTS167. C4‐2b cells were treated with vehicle or 30 nM OTS167 for 2 h, and phosphoproteins were analysed using a Phospho Explorer Antibody Array. Signals for each phosphorylation site were normalised to its corresponding total protein. Results for all phosphorylation sites on p90RSK and its known target sites that were analysed and exhibited a log2FC of 0.5 or greater are shown.OTS167 reduces phosphorylation of stathmin in vivo. Protein was extracted from xenograft tissue of vehicle or OTS167‐treated mice, and total and phosphorylated levels of stathmin were determined by Western blot. Due to the extremely small size and high degree of cell death in OTS167‐treated xenograft tumours, only four samples in the drug‐treated group yielded lysates of sufficient quality.Individual growth curves of xenograft tumours as determined by calliper measurements are shown. Growth curves corresponding to samples in (D) are shown in brighter colours and individually labelled.Silencing of MELK reduces phosphorylation of stathmin at Ser‐38. C4‐2b cells were transfected with siRNAs directed against MELK for 72 h, and levels of total and phosphorylated stathmin were determined by Western blot analysis. β‐Actin was used as a loading control. Source data are available online for this figure.